Taxonomic analysis with percent

Preparation

Paths and libraries setting

# Load main packages, paths and custom functions
source("../../../source/main_packages.R")
source("../../../source/functions.R")

# Load supplementary packages
packages <- c("RColorBrewer", "ggpubr", "cowplot")
invisible(lapply(packages, require, character.only = TRUE))

Load phyloseq object after decontam

ps.filter <- readRDS("../../../../output/1_MED/1D/1D_MED_phyloseq_decontam.rds")
df <- psmelt(ps.filter)
colnames(df)[colnames(df) %in% "sample_Species"] <- "Species.x"

Setting plot display

# new names for Genus
new_names_genus <- c("Wolbachia",
               "Asaia",
               "Legionella",
               "Elizabethkingia",
               "Chryseobacterium",
               "Erwinia",
               "Morganella",
               "Pseudomonas",
               "Delftia",
               "Methylobacterium-Methylorubrum",
               "Serratia",
               "Coetzeea",
               "NA"
)

# col for Genus
col_genus <- c("Wolbachia"="#FEB24C",
               "Asaia"="#10E015",
               "Legionella"="#DE3F23",
               "Elizabethkingia"="#66A7ED",
               "Chryseobacterium"="#F899FF",
               "Erwinia"="#FFE352",
               "Morganella"="#F5E4D3",
               "Pseudomonas"="#DBF5F0",
               "Delftia"="#C7C5B7",
               "Methylobacterium-Methylorubrum"="blue",
               "Serratia"="#B136F5",
               "Coetzeea"="red",
               "NA"="grey")

# param for plot
guide_italics <- guides(fill = guide_legend(label.theme = element_text(size = 10, face = "italic", colour = "Black", angle = 0)))

# labels
make.italic <- function(x) as.expression(lapply(x, function(y) bquote(italic(.(y)))))
labels = c("Wolbachia"=make.italic("Wolbachia"),
                      "Asaia"=make.italic("Asaia"),
                      "Legionella"=make.italic("Legionella"),
                      "Elizabethkingia"=make.italic("Elizabethkingia"),
                      "Chryseobacterium"=make.italic("Chryseobacterium"),
                      "Erwinia"=make.italic("Erwinia"),
                      "Morganella"=make.italic("Morganella"),
                      "Pseudomonas"=make.italic("Pseudomonas"),
                      "Delftia"=make.italic("Delftia"),
                      "Methylobacterium-Methylorubrum"=make.italic("Methylobacterium-Methylorubrum"),
                      "Serratia"=make.italic("Serratia"),
                      "Coetzeea"=make.italic("Coetzeea"),
                      "NA"
)

Taxonomic % plots

Culex pipiens

Whole

df_plot <- df[df$Species.x=="Culex pipiens" & df$Organ=="Whole",] %>%
  group_by(Species.x, Genus) %>%
  summarise(read_sum = sum(Abundance))
## `summarise()` regrouping output by 'Species.x' (override with `.groups` argument)
df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Species.x,-percent)),]

df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)

df_plot <- droplevels(df_plot)

pipiens1 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
  geom_bar(position = "dodge", stat = "identity")+
  scale_fill_manual(values = col_genus)+
  theme_bw() +
  theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
  ggtitle("") +
  guide_italics+
  theme(legend.title = element_text(size = 18), legend.position="bottom")+
  theme(panel.spacing=unit(0,"lines"),
        strip.background=element_rect(color="grey30", fill="grey90"),
        panel.border=element_rect(color="grey90"),
        plot.title=element_text(size=10),
        axis.ticks.x=element_blank()) +
  geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
  scale_y_continuous(breaks=seq(0,105, by=10))+
  scale_x_discrete(labels = labels)+
  ylim(0,100)+
  labs(title="All strains", x="Genus", y="Relative abundance (%)", subtitle= "Culex pipiens - Whole")+
  theme(plot.tag.position = "topright",
        plot.subtitle=element_text(size=10, face="italic", color="black"))
## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.
pipiens1

Whole - Bosc

df_plot <- df[df$Species.x=="Culex pipiens" & df$Organ=="Whole" & df$Strain=="Field - Bosc",] %>%
  group_by(Strain, Genus) %>%
  summarise(read_sum = sum(Abundance))
## `summarise()` regrouping output by 'Strain' (override with `.groups` argument)
df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Strain,-percent)),]

df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)

df_plot <- droplevels(df_plot)

pipiens2 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
  geom_bar(position = "dodge", stat = "identity")+
  scale_fill_manual(values = col_genus)+
  theme_bw() +
  theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
  ggtitle("") +
  guide_italics+
  theme(legend.title = element_text(size = 18), legend.position="bottom")+
  theme(panel.spacing=unit(0,"lines"),
        strip.background=element_rect(color="grey30", fill="grey90"),
        panel.border=element_rect(color="grey90"),
        plot.title=element_text(size=10),
        axis.ticks.x=element_blank()) +
  geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
  scale_y_continuous(breaks=seq(0,105, by=10))+
  scale_x_discrete(labels = labels)+
  ylim(0,100)+
  labs(title="Field - Bosc", x="Genus", y="Relative abundance (%)", subtitle= "Culex pipiens - Whole")+
  theme(plot.tag.position = "topright",
        plot.subtitle=element_text(size=10, face="italic", color="black"))
## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.
pipiens2

Whole - Camping Europe

df_plot <- df[df$Species.x=="Culex pipiens" & df$Organ=="Whole" & df$Strain=="Field - Camping Europe",] %>%
  group_by(Strain, Genus) %>%
  summarise(read_sum = sum(Abundance))
## `summarise()` regrouping output by 'Strain' (override with `.groups` argument)
df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Strain,-percent)),]

df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)

df_plot <- droplevels(df_plot)

pipiens3 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
  geom_bar(position = "dodge", stat = "identity")+
  scale_fill_manual(values = col_genus)+
  theme_bw() +
  theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
  ggtitle("") +
  guide_italics+
  theme(legend.title = element_text(size = 18), legend.position="bottom")+
  theme(panel.spacing=unit(0,"lines"),
        strip.background=element_rect(color="grey30", fill="grey90"),
        panel.border=element_rect(color="grey90"),
        plot.title=element_text(size=10),
        axis.ticks.x=element_blank()) +
  geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
  scale_y_continuous(breaks=seq(0,105, by=10))+
  scale_x_discrete(labels = labels)+
  ylim(0,100)+
  labs(title="Field - Camping Europe", x="Genus", y="Relative abundance (%)", subtitle= "Culex pipiens - Whole")+
  theme(plot.tag.position = "topright",
        plot.subtitle=element_text(size=10, face="italic", color="black"))
## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.
pipiens3

Whole - Lavar

df_plot <- df[df$Species.x=="Culex pipiens" & df$Organ=="Whole" & df$Strain=="Laboratory - Lavar",] %>%
  group_by(Strain, Genus) %>%
  summarise(read_sum = sum(Abundance))
## `summarise()` regrouping output by 'Strain' (override with `.groups` argument)
df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Strain,-percent)),]

df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)

df_plot <- droplevels(df_plot)

pipiens4 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
  geom_bar(position = "dodge", stat = "identity")+
  scale_fill_manual(values = col_genus)+
  theme_bw() +
  theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
  ggtitle("") +
  guide_italics+
  theme(legend.title = element_text(size = 18), legend.position="bottom")+
  theme(panel.spacing=unit(0,"lines"),
        strip.background=element_rect(color="grey30", fill="grey90"),
        panel.border=element_rect(color="grey90"),
        plot.title=element_text(size=10),
        axis.ticks.x=element_blank()) +
  geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
  scale_y_continuous(breaks=seq(0,105, by=10))+
  scale_x_discrete(labels = labels)+
  ylim(0,100)+
  labs(title="Laboratory - Lavar", x="Genus", y="Relative abundance (%)", subtitle= "Culex pipiens - Whole")+
  theme(plot.tag.position = "topright",
        plot.subtitle=element_text(size=10, face="italic", color="black"))
## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.
pipiens4

Ovary

df_plot <- df[df$Species.x=="Culex pipiens" & df$Organ=="Ovary",] %>%
  group_by(Species.x, Genus) %>%
  summarise(read_sum = sum(Abundance))
## `summarise()` regrouping output by 'Species.x' (override with `.groups` argument)
df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Species.x,-percent)),]

df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)

df_plot <- droplevels(df_plot)

pipiens5 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
  geom_bar(position = "dodge", stat = "identity")+
  scale_fill_manual(values = col_genus)+
  theme_bw() +
  theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
  ggtitle("") +
  guide_italics+
  theme(legend.title = element_text(size = 18), legend.position="bottom")+
  theme(panel.spacing=unit(0,"lines"),
        strip.background=element_rect(color="grey30", fill="grey90"),
        panel.border=element_rect(color="grey90"),
        plot.title=element_text(size=10),
        axis.ticks.x=element_blank()) +
  geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
  scale_y_continuous(breaks=seq(0,105, by=10))+
  scale_x_discrete(labels = labels)+
  ylim(0,100)+
  labs(title="All strains", x="Genus", y="Relative abundance (%)", subtitle= "Culex pipiens - Ovary")+
  theme(plot.tag.position = "topright",
        plot.subtitle=element_text(size=10, face="italic", color="black"))
## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.
pipiens5

Groups

# Plot
p_pipiens <- plot_grid(pipiens1+ theme(legend.position="none"), 
          pipiens2+ theme(legend.position="none"), 
          pipiens3+ theme(legend.position="none"), 
          pipiens4+ theme(legend.position="none"), 
          pipiens5+ theme(legend.position="none", plot.margin = unit(c(0.17,-1,1.2,0), "cm")),
          ncol = 5, 
          nrow = 2)

Culex quinquefasciatus

Whole

df_plot <- df[df$Species.x=="Culex quinquefasciatus" & df$Organ=="Whole",] %>%
  group_by(Species.x, Genus) %>%
  summarise(read_sum = sum(Abundance))
## `summarise()` regrouping output by 'Species.x' (override with `.groups` argument)
df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Species.x,-percent)),]

df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)

df_plot <- droplevels(df_plot)

quinque1 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
  geom_bar(position = "dodge", stat = "identity")+
  scale_fill_manual(values = col_genus)+
  theme_bw() +
  theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
  ggtitle("") +
  guide_italics+
  theme(legend.title = element_text(size = 18), legend.position="bottom")+
  theme(panel.spacing=unit(0,"lines"),
        strip.background=element_rect(color="grey30", fill="grey90"),
        panel.border=element_rect(color="grey90"),
        plot.title=element_text(size=10),
        axis.ticks.x=element_blank()) +
  geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
  scale_y_continuous(breaks=seq(0,105, by=10))+
  scale_x_discrete(labels = labels)+
  ylim(0,100)+
  labs(title="All strains", x="Genus", y="Relative abundance (%)", subtitle= "Culex quinquefasciatus - Whole")+
  theme(plot.tag.position = "topright",
        plot.subtitle=element_text(size=10, face="italic", color="black"))
## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.
quinque1

Whole - Guadeloupe

df_plot <- df[df$Species.x=="Culex quinquefasciatus" & df$Organ=="Whole" & df$Strain=="Field - Guadeloupe",] %>%
  group_by(Strain, Genus) %>%
  summarise(read_sum = sum(Abundance))
## `summarise()` regrouping output by 'Strain' (override with `.groups` argument)
df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Strain,-percent)),]

df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)

df_plot <- droplevels(df_plot)

quinque2 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
  geom_bar(position = "dodge", stat = "identity")+
  scale_fill_manual(values = col_genus)+
  theme_bw() +
  theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
  ggtitle("") +
  guide_italics+
  theme(legend.title = element_text(size = 18), legend.position="bottom")+
  theme(panel.spacing=unit(0,"lines"),
        strip.background=element_rect(color="grey30", fill="grey90"),
        panel.border=element_rect(color="grey90"),
        plot.title=element_text(size=10),
        axis.ticks.x=element_blank()) +
  geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
  scale_y_continuous(breaks=seq(0,105, by=10))+
  scale_x_discrete(labels = labels)+
  ylim(0,100)+
  labs(title="Field - Guadeloupe", x="Genus", y="Relative abundance (%)", subtitle= "Culex quinquefasciatus - Whole")+
  theme(plot.tag.position = "topright",
        plot.subtitle=element_text(size=10, face="italic", color="black"))
## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.
quinque2

Whole - Slab TC

df_plot <- df[df$Species.x=="Culex quinquefasciatus" & df$Organ=="Whole" & df$Strain=="Laboratory - Slab TC (Wolbachia -)",] %>%
  group_by(Strain, Genus) %>%
  summarise(read_sum = sum(Abundance))
## `summarise()` regrouping output by 'Strain' (override with `.groups` argument)
df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Strain,-percent)),]

df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)

df_plot <- droplevels(df_plot)

quinque3 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
  geom_bar(position = "dodge", stat = "identity")+
  scale_fill_manual(values = col_genus)+
  theme_bw() +
  theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
  ggtitle("") +
  guide_italics+
  theme(legend.title = element_text(size = 18), legend.position="bottom")+
  theme(panel.spacing=unit(0,"lines"),
        strip.background=element_rect(color="grey30", fill="grey90"),
        panel.border=element_rect(color="grey90"),
        plot.title=element_text(size=10),
        axis.ticks.x=element_blank()) +
  geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
  scale_y_continuous(breaks=seq(0,105, by=10))+
  scale_x_discrete(labels = labels)+
  ylim(0,100)+
  labs(title="Laboratory - Slab TC (Wolbachia -)", x="Genus", y="Relative abundance (%)", subtitle= "Culex quinquefasciatus - Whole")+
  theme(plot.tag.position = "topright",
        plot.subtitle=element_text(size=10, face="italic", color="black"))
## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.
quinque3

Ovary

df_plot <- df[df$Species.x=="Culex quinquefasciatus" & df$Organ=="Ovary",] %>%
  group_by(Species.x, Genus) %>%
  summarise(read_sum = sum(Abundance))
## `summarise()` regrouping output by 'Species.x' (override with `.groups` argument)
df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Species.x,-percent)),]

df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)

df_plot <- droplevels(df_plot)

quinque4 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
  geom_bar(position = "dodge", stat = "identity")+
  scale_fill_manual(values = col_genus)+
  theme_bw() +
  theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
  ggtitle("") +
  guide_italics+
  theme(legend.title = element_text(size = 18), legend.position="bottom")+
  theme(panel.spacing=unit(0,"lines"),
        strip.background=element_rect(color="grey30", fill="grey90"),
        panel.border=element_rect(color="grey90"),
        plot.title=element_text(size=10),
        axis.ticks.x=element_blank()) +
  geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
  scale_y_continuous(breaks=seq(0,105, by=10))+
  scale_x_discrete(labels = labels)+
  ylim(0,100)+
  labs(title="All strains", x="Genus", y="Relative abundance (%)", subtitle= "Culex quinquefasciatus - Ovary")+
  theme(plot.tag.position = "topright",
        plot.subtitle=element_text(size=10, face="italic", color="black"))
## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.
quinque4

Groups

# Plot
p_quinque <- plot_grid(quinque1+ theme(legend.position="none"), 
          quinque2+ theme(legend.position="none"), 
          quinque3+ theme(legend.position="none"), 
          quinque4+ theme(legend.position="none", plot.margin = unit(c(0.17,0,1.2,0), "cm")), 
          plot.new(),
          ncol = 5, 
          nrow = 2)

p_quinque

Aedes aegyti

Whole

df_plot <- df[df$Species.x=="Aedes aegypti" & df$Organ=="Whole",] %>%
  group_by(Species.x, Genus) %>%
  summarise(read_sum = sum(Abundance))
## `summarise()` regrouping output by 'Species.x' (override with `.groups` argument)
df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Species.x,-percent)),]

df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)

df_plot <- droplevels(df_plot)

aedes1 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
  geom_bar(position = "dodge", stat = "identity")+
  scale_fill_manual(values = col_genus)+
  theme_bw() +
  theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
  ggtitle("") +
  guide_italics+
  theme(legend.title = element_text(size = 18), legend.position="bottom")+
  theme(panel.spacing=unit(0,"lines"),
        strip.background=element_rect(color="grey30", fill="grey90"),
        panel.border=element_rect(color="grey90"),
        plot.title=element_text(size=10),
        axis.ticks.x=element_blank()) +
  geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
  scale_y_continuous(breaks=seq(0,105, by=10))+
  scale_x_discrete(labels = labels)+
  ylim(0,100)+
  labs(title="All strains", x="Genus", y="Relative abundance (%)", subtitle= "Aedes aegytpi - Whole")+
  theme(plot.tag.position = "topright",
        plot.subtitle=element_text(size=10, face="italic", color="black"))
## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.
aedes1

Ovary

df_plot <- df[df$Species.x=="Aedes aegypti" & df$Organ=="Ovary",] %>%
  group_by(Species.x, Genus) %>%
  summarise(read_sum = sum(Abundance))
## `summarise()` regrouping output by 'Species.x' (override with `.groups` argument)
df_plot$percent <- (df_plot$read_sum/sum(df_plot$read_sum))*100
df_plot <- df_plot[with(df_plot, order(Species.x,-percent)),]

df_plot$Genus <- factor(df_plot$Genus, levels = unique(df_plot$Genus))
df_plot$Genus <- factor(df_plot$Genus, levels = new_names_genus)

df_plot <- droplevels(df_plot)

aedes2 <- ggplot(df_plot, aes(x=Genus, y=percent, fill = Genus))+
  geom_bar(position = "dodge", stat = "identity")+
  scale_fill_manual(values = col_genus)+
  theme_bw() +
  theme(axis.text.x = element_text(angle = 45, vjust=1, hjust=1, size=12))+
  ggtitle("") +
  guide_italics+
  theme(legend.title = element_text(size = 18), legend.position="bottom")+
  theme(panel.spacing=unit(0,"lines"),
        strip.background=element_rect(color="grey30", fill="grey90"),
        panel.border=element_rect(color="grey90"),
        plot.title=element_text(size=10),
        axis.ticks.x=element_blank()) +
  geom_text(aes(label=percent %>% round(1)),position=position_dodge(width=0.9), vjust=-0.25, size=4)+
  scale_y_continuous(breaks=seq(0,105, by=10))+
  scale_x_discrete(labels = labels)+
  ylim(0,100)+
  labs(title="All strains", x="Genus", y="Relative abundance (%)", subtitle= "Aedes aegytpi - Ovary")+
  theme(plot.tag.position = "topright",
        plot.subtitle=element_text(size=10, face="italic", color="black"))
## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.
aedes2

Groups

# Plot
p_aedes <- plot_grid(aedes1+ theme(legend.position="none"), 
                     aedes2+ theme(legend.position="none", plot.margin = unit(c(0.17,0,1.2,0), "cm")), 
                     plot.new(),
                     plot.new(),
                     plot.new(),
                     ncol = 5, 
                     nrow = 2)

Plot with all

p_global <- plot_grid(pipiens1+ theme(legend.position="none"), 
                     pipiens2+ theme(legend.position="none"), 
                     pipiens3+ theme(legend.position="none"), 
                     pipiens4+ theme(legend.position="none"), 
                     pipiens5+ theme(legend.position="none", plot.margin = unit(c(0.17,1,1.2,0), "cm")),
                     quinque1+ theme(legend.position="none"), 
                     quinque2+ theme(legend.position="none"), 
                     quinque3+ theme(legend.position="none"), 
                     quinque4+ theme(legend.position="none", plot.margin = unit(c(0.17,1,1.2,0), "cm")), 
                     plot.new(),
                     aedes1+ theme(legend.position="none"), 
                     #aedes2+ theme(legend.position="none", plot.margin = unit(c(0.17,1,1.2,0), "cm")), 
                     plot.new(),
                     plot.new(),
                     plot.new(),
                     nrow=3, 
                     ncol=5
)

p_global

Save plots

tiff("../../../../output/1_MED/1E/1Ef_MED_taxonomic_percent.tiff", units="in", width=25, height=20, res=300)
p_global
dev.off()
## quartz_off_screen 
##                 2
tiff("../../../../output/1_MED/1E/1Ef_MED_taxonomic_percent.png", units="in", width=25, height=20, res=300)
p_global
dev.off()
## quartz_off_screen 
##                 2

Session info

sessionInfo()
## R version 3.6.3 (2020-02-29)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS  10.16
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] fr_FR.UTF-8/fr_FR.UTF-8/fr_FR.UTF-8/C/fr_FR.UTF-8/fr_FR.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] cowplot_1.1.0      ggpubr_0.4.0       RColorBrewer_1.1-2 forcats_0.5.0     
##  [5] stringr_1.4.0      dplyr_1.0.2        purrr_0.3.4        readr_1.4.0       
##  [9] tidyr_1.1.2        tibble_3.0.4       tidyverse_1.3.0    ggplot2_3.3.2     
## [13] phyloseq_1.30.0   
## 
## loaded via a namespace (and not attached):
##   [1] nlme_3.1-149        fs_1.5.0            lubridate_1.7.9    
##   [4] httr_1.4.2          tools_3.6.3         backports_1.1.10   
##   [7] bslib_0.2.4         R6_2.4.1            vegan_2.5-6        
##  [10] DBI_1.1.0           BiocGenerics_0.32.0 mgcv_1.8-33        
##  [13] colorspace_2.0-0    permute_0.9-5       ade4_1.7-15        
##  [16] withr_2.3.0         tidyselect_1.1.0    curl_4.3           
##  [19] compiler_3.6.3      cli_2.1.0           rvest_0.3.6        
##  [22] Biobase_2.46.0      xml2_1.3.2          labeling_0.4.2     
##  [25] bookdown_0.22       sass_0.3.1          scales_1.1.1       
##  [28] digest_0.6.26       foreign_0.8-75      rmarkdown_2.7      
##  [31] rio_0.5.16          XVector_0.26.0      pkgconfig_2.0.3    
##  [34] htmltools_0.5.1.1   dbplyr_1.4.4        rlang_0.4.10       
##  [37] readxl_1.3.1        rstudioapi_0.11     farver_2.0.3       
##  [40] jquerylib_0.1.3     generics_0.0.2      jsonlite_1.7.1     
##  [43] zip_2.1.1           car_3.0-10          magrittr_1.5       
##  [46] biomformat_1.14.0   Matrix_1.2-18       fansi_0.4.1        
##  [49] Rcpp_1.0.5          munsell_0.5.0       S4Vectors_0.24.4   
##  [52] Rhdf5lib_1.8.0      abind_1.4-5         ape_5.4-1          
##  [55] lifecycle_0.2.0     stringi_1.5.3       yaml_2.2.1         
##  [58] carData_3.0-4       MASS_7.3-53         zlibbioc_1.32.0    
##  [61] rhdf5_2.30.1        plyr_1.8.6          grid_3.6.3         
##  [64] blob_1.2.1          parallel_3.6.3      crayon_1.3.4       
##  [67] lattice_0.20-41     Biostrings_2.54.0   haven_2.3.1        
##  [70] splines_3.6.3       multtest_2.42.0     hms_0.5.3          
##  [73] ps_1.4.0            knitr_1.30          pillar_1.4.6       
##  [76] igraph_1.2.6        ggsignif_0.6.0      reshape2_1.4.4     
##  [79] codetools_0.2-16    stats4_3.6.3        reprex_0.3.0       
##  [82] glue_1.4.2          evaluate_0.14       data.table_1.13.2  
##  [85] modelr_0.1.8        vctrs_0.3.4         rmdformats_1.0.2   
##  [88] foreach_1.5.1       cellranger_1.1.0    gtable_0.3.0       
##  [91] assertthat_0.2.1    openxlsx_4.2.3      xfun_0.22          
##  [94] broom_0.7.2         rstatix_0.6.0       survival_3.2-7     
##  [97] iterators_1.0.13    IRanges_2.20.2      cluster_2.1.0      
## [100] ellipsis_0.3.1